This article investigates robust design methodologies for cost-effective and resilient design of filterless Point-to-Multipoint (P2MP) optical networks by minimizing the number of amplifiers, which are often compromised by parameter uncertainties, for example inaccurate fiber loss. To overcome the inefficiencies of traditional, overly or insufficiently conservative margin-based designs, this study investigates Deterministic Optimization (DO), Robust Optimization (RO), and Adjustable Robust Optimization (ARO) of optical filterless horseshoe networks. All these techniques are explained in detail using a simple Linear Program (LP) model example. The findings of this manuscript demonstrate that ARO is a significantly superior technique, leveraging a two-stage, “wait-and-see” approach that allows for adaptive adjustments, by modifying amplifier gains after uncertainty is revealed. This adaptability reduces the conservatism of standard RO, achieving full resiliency with a much lower “price of robustness”. Specifically, for the considered scenarios, at a 20% uncertainty level, ARO required only a 16% increase in amplifiers compared to 40% for RO, ultimately providing a more efficient trade-off between performance and robustness.

While horseshoe filterless networks with point-to-multipoint (P2MP) transceivers offer a cost-effective solution with inherent survivability against single-link failures, certain scenarios may demand an even higher degree of network resilience. This is particularly true in regions with frequent power outages and/or where load shedding is enforced. Addressing this problem requires a careful design and trade-off between survivability and cost. This paper describes a multi-objective optimization framework based on Integer Linear Programming (ILP) that accurately models the problem and can be used to obtain solutions that prioritize one or the other metric. Moreover, the paper reports a study using a set of randomly generated horseshoe topologies that demonstrates how strategically placing amplifiers and unbalanced couplers can significantly enhance network resilience, while also keeping the minimum number of additional optical amplifiers required.

Horseshoe filterless networks with point-to-multipoint (P2MP) transceivers are cost-effective but may lack resilience in regions with power outages. This paper addresses this gap by strategically placing amplifiers and couplers to enhance network resiliency. We evaluate the effectiveness of this approach through a network availability analysis.

This paper proposes an Integer Linear Programming (ILP) framework to optimize the multi-period planning of metro-aggregation networks exploiting both point-to-multipoint coherent pluggable transceivers and a filterless line system architecture. We investigate several planning strategies to minimize cost while also considering traffic prediction and operational expenditures. The results of a reference network provide evidence of transceiver cost reductions between 20% and 32% compared to the point-to-point approach over a five-year planning period.

Emerging applications are driving traffic requirements to new heights, from IoT and autonomous driving to augmented reality and Industry 4.0. Urban areas, which have a significant fraction of the telecom infrastructure capital expenditures (CAPEX), are experiencing even more growth than other segments. Noteworthy, the traffic pattern in aggregation networks is hub-and-leaf, with only a few hub nodes communicating with multiple leaf nodes. Traditional point-to-point optical solutions are not the best fit for this pattern. A novel optical technology enabling point-to-multipoint operation has recently been proposed to address this limitation. Since this solution relies on broadcasting the optical signal over a virtual tree, its optimal deployment in generic fiber topologies (with failure survivability conditions) requires specific designs. This paper describes an integer linear programming model to optimize the design of survivable metro-aggregation networks exploiting point-to-multipoint coherent transceivers. Results obtained on a mesh network show evidence that transceiver expenditures can be reduced by a figure between 25% and 60%.

The ever-increasing traffic requirements need cost-efficient and reliable solutions. Metropolitan networks are responsible for a large fraction of the telecom infrastructure CAPEX. Albeit the traffic pattern in these networks tends to be hub-and-spoke, the current transceiver deployments do not leverage this feature. This paper describes and models various survivable metro-aggregation network scenarios using point-to-multipoint capable coherent transceivers. The results obtained over a reference mesh network show that these transceivers can reduce total transceiver costs by ~40% on average.